code: def main(config):
      model = build_model(config["arch"])
      load_checkpoint(model, config["trainer"]["resume_checkpoint"])
      model.eval()
  
      save_path = config["trainer"]["output_dir"]
      save_path = os.path.join(save_path, "inference")
      infer_shape = [3, -1, -1]
      model = to_static(
          model,
          input_spec=[
              paddle.static.InputSpec(
                  shape=[None] + infer_shape, dtype="float32"
              )
          ],
      )
  
      paddle.jit.save(model, save_path)
      print("inference model is saved to {}".format(save_path))
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/tools/export_model.py
imports: import os
  import sys
  import argparse
  import paddle
  from paddle.jit import to_static
  from models import build_model
  from utils import Config, ArgsParser
label_desc: Use image node_id 3 for calling a global function with example usage: main(config) without return types